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Building Llama 3 LLM from scratch in code AI Beginners Guide In the “Advanced settings”, it’s possible to fine-tune hyperparameters, such as temperature, repetition penalty, or the number of top-k tokens to consider when generating text. Training also entails exposing it to the preprocessed dataset and repeatedly updating its parameters to minimize the difference between the predicted model’s output and the actual output. This process, known as backpropagation, allows your model to learn about underlying patterns and relationships within the data. For this task, you’re in good hands with Python, which provides a wide range of libraries and frameworks commonly used in NLP and ML, such as TensorFlow, PyTorch, and Keras. These libraries offer prebuilt modules and functions that simplify the implementation of complex architectures and training procedures. Additionally, your programming skills will enable you to customize and adapt your existing model to suit specific requirements